Local inference is just hoarding with better marketing
The rush to run everything locally isn't about privacy or cost savings, it's about control anxiety in a world where APIs actually work better.
We’re watching an entire industry convince itself that running models on RTX cards is revolutionary progress. It’s not. It’s digital prepping dressed up as technical innovation.
The convenience myth
Local inference advocates bang on about avoiding “token taxes” like they’re fighting some noble war against cloud tyranny. Meanwhile, they’re spending thousands on hardware that becomes obsolete faster than their gaming rigs. The maths doesn’t add up unless you’re planning to run millions of tokens monthly, which most developers aren’t.
APIs work. They’re fast, reliable, and someone else deals with the infrastructure headaches. The real cost isn’t tokens, it’s the engineering hours spent debugging CUDA drivers and managing model weights.
Control theatre
The privacy argument falls apart when you examine what people actually do with local models. They’re not processing state secrets or medical records. They’re building chatbots and content generators that could run perfectly well in the cloud.
This obsession with local control stems from the same anxiety that drives people to download movies they’ll never watch. It feels safer to own it, even when streaming is objectively better.
The real infrastructure problem
The energy and hardware requirements for widespread local deployment are genuinely mental. Every developer running their own Llama instance is less efficient than shared cloud infrastructure by orders of magnitude.
We’re optimising for the wrong thing. The bottleneck isn’t API costs or latency. It’s building systems that actually solve problems instead of systems that feel politically correct.